Initial project feasibility study

To do

•            Information Gathering 
•            System States Descriptions 
•            Possible Decitions 
•            Quality Measure 
•            Rewards/ Expected Performance 

Findings 

Project title: Investigating improving the drill ship's mining rate with an autonomous mining path predicting Machine Learning Model.

Project description: using the historic and current mining time series data and environmental parameters to create a Machine learning model than will perform a few days/ a week's mining rate performance forecast.

Key areas:

-Mining Rate = Area covered 

                      Time

-Overlaps   

            

when mining, only 60 to 70% overlap is preferred for material extraction  

-RPM (Revolutions Per Minute) How fast the drill tool is rotating 

Preliminary mining parameters to consider:

Depth penetration

Torque

Weight on bit 

Vessel movement efficiency

3D data

Hydrophone data

Weather prediction

Geology 

    lithology 

Direction 

    North, South, Inshore, and Offshore 

Notes:

• Quick drill tool lift up is 8 meters and drop for eight meters 
• Vessel movement efficiency should be considered.
• Considered Pre-move data 
• Environmental factors 

Next:

Draft Gantt Chart 

Get Supervisor Approval